Is there any research on how accurately people can follow a beat?

Is there any research on how accurately people can follow a beat?

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I'm currently helping develop a rhythm game, and as part of the scoring system, I'd like to make scores and ranks based more on accurate pattern recognition rather than hitting notes very exactly on time as is the case for many games of this variety.

In many cases, the margin of error for the best judgment in rhythm games is so small that it seems to be a matter of chance more than skill that a certain judgment is counted between "excellent" and "good" (for example, one game has the margin as small as ±0.011 s).

Of course, some people are better at hitting notes accurately than others either naturally or through practice, but I would like to find some actual research into what the base neurological limitations to rhythmic precision are and to what degree practice can actually improve it.

As a baseline benchmark for the best judgment, I was thinking of looking for some research into how accurately people can follow the tick of a metronome - for example, by measuring the average deviation of somebody tapping a button to a regular beat after about 100 beats or so when they've gotten used to it.

A Google search didn't return anything useful, probably because the search terms draw up so much other, irrelevant content. Is there any prior research on this subject? If so, where can I find it? If not, how could I conduct such an experiment myself?

You might begin your search with the characteristics of Parkinson's disease. This degenerative disorder is precipitated by the death of neurons in the substantia niagra. This brain structure is composed of multiple neurological nuclei. Its function is to connect cortical regions and nuclei together, most significantly with the basal ganglia. The difference between nuclei and cortical brain circuits is important to your question.

The symptoms of Parkinson's are directly correlated with the function of nuclei in central nervous system: the integration of information. It's the integration of conscious thought, muscle memory, sensory-motor pathways that makes voluntary movement possible. Disruption of this network in Parkinson's degrades one's ability to voluntarily execute a movement.

The cerebellum also controls voluntary movement. As a cortical structure, it is involved more with the formation and maintenance of muscle memory than information integration. Damage here results in the loss of fine motor control as opposed to gross motor control in Parkinson's.

This problem has a sensory and motor component. It might be difficult to tackle your problem as a whole. Perhaps breaking it down into smaller pieces would shed some light on what you're looking for.

Here are 2 articles I found relating motor control with the cerebellum and substantia niagra.

Relating cerebellar damage with learning sequence information

Relating the substantia niagra with interval timing

In performing a cursory Google Scholar search using the terms "keeping tempo", I found these articles that seem to cover your topic of interest:

Schulze, Cordes, and Vorberg (2005) Keeping Synchrony While Tempo Changes: Accelerando and Ritardando

Scheirer (1997) Tempo and beat analysis of acoustic musical signals

McKinnet and Moelants (2006) Ambiguity in Tempo Perception: What Draws Listeners to Different Metrical Levels?

Hopefully, these papers are a help to you. It doesn't hurt to conduct experiments that others have conducted. All that really does is add more information and data to what is currently available/known.

These manuscripts should present well-rounded studies reporting innovative advances that further knowledge about a topic of importance to the fields of biology or medicine. The conclusions of the Original Research Article should clearly be supported by the results. These can be submitted as either a full-length article (no more than 6,000 words, 8 figures, and 4 tables) or a brief communication (no more than 2,500 words, 3 figures, and 2 tables). Original Research Articles contain five sections: abstract, introduction, materials and methods, results and discussion.

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Whilst perfect in principle, there are a number of problems with this type of design. Firstly, they can be almost too perfect, with the conditions being under complete control and not being representative of real world conditions.

For psychologists and behavioral biologists, for example, there can never be any guarantee that a human or living organism will exhibit ‘normal’ behavior under experimental conditions.

True experiments can be too accurate and it is very difficult to obtain a complete rejection or acceptance of a hypothesis because the standards of proof required are so difficult to reach.

True experiments are also difficult and expensive to set up. They can also be very impractical.

While for some fields, like physics, there are not as many variables so the design is easy, for social sciences and biological sciences, where variations are not so clearly defined it is much more difficult to exclude other factors that may be affecting the manipulated variable.

The Consequences of Procrastination

Procrastination may relieve pressure in the moment, but it can have steep emotional, physical, and practical costs. Students who routinely procrastinate tend to get lower grades, workers who procrastinate produce lower-quality work, and in general, habitual procrastinators can experience reduced well-being in the form of insomnia or immune system and gastrointestinal disturbance. Procrastination can also jeopardize both personal and professional relationships.

Is procrastination bad for my health?

Procrastinating when it comes to one’s health—putting off exercise and checkups, and failing to commit to healthy eating—can lead to a higher risk of hypertension and cardiovascular disease. Procrastinators are also more likely to engage in self-blame and disengage from wellness advice, suggesting that cultivating greater self-compassion could help such individuals begin taking better care of themselves.

Is there a link between procrastination and depression?

Procrastination, avoidance, and rumination are all common symptoms of depression. People with depression may struggle to plan ahead, lose confidence in their ability to follow through, and adopt “what’s the point” thinking. The treatment approach known as behavioral activation, in which one schedules enjoyable activities that provide a sense of mastery or accomplishment, may help alleviate some of these effects.

Can procrastinators have successful relationships with non-procrastinators?

When a procrastinator enters a relationship with a non-procrastinator, conflict is almost inevitable: Each places a very different value on their time, believes their approach is superior, and struggles to understand the other’s motivations. As with any other conflict, though, stepping back, considering the other’s perspective, and finding a way to accept it, and one’s own reaction to it, can help keep a couple together.

An Example

While there are some regional large scale-studies such as the HUNT-study or the Decode Genetics of Iceland-study, in reality it is usually not possible to sample the whole population, due to budget, time limits and feasibility.

For example, you may want to test a hypothesis about the effect of an educational program on schoolchildren in the US.

For the perfect experiment, you would test every single child in the US using the program, against a control group. If this number runs into the millions, this may not be possible without a huge number of researchers and a bottomless pit of money.

Thus, in order to generalize you need to select a sample group that is representative of the whole population.

1. Representativeness

A high budget research project might take a smaller sample from every school in the country a lower budget operation may have to concentrate upon one city or even a single school.

The key to generalization is to understand how much your results can be applied backwards to represent the group of US children, as a whole. The first example, using every school, would be strongly representative, because the range and number of samples is high. These samples more closely resembles the population they are trying to study. Testing only one school makes generalization difficult and affects the external validity.

You might find that one school generates worse than average results for children using that particular educational program. However, a school in the next town might contain children who do better. The students may be from a completely different socioeconomic background or culture.

Critics of your results will pounce upon such discrepancies and question your entire experimental design. At best, you can now only generalize to that particular school, and cannot legitimately make any conclusions about all US school children.

2. Time effects

Representativeness is not just about the qualities of the population, but those qualities at a particular time.

Large sample groups could be gathered from schools all across the US. But if one sample is tested at the beginning of the year and the other group at the end, the groups now differ from one another. Perhaps the latter children perform better simply because they are now slightly older than the former.

Good experiments consider the element of time and design research to minimize its effects.

3. Sample size

The smaller a sample gets, the less likely it is to be representative. For example, let’s say that 1% of all US children would have done extremely well on the educational program. This is 1 in 100 children. If your sample size happens to only be 60 children, your sample may not contain a child who is likely to do very well in the program. Your sample is less representative because it is smaller. Your results will be different depending on whether your sample contains one of these children or not.

Most statistical tests contain an inbuilt mechanism to take into account sample sizes with larger groups and numbers, leading to results that are more significant.

The problem is that they cannot distinguish the validity of the results, and determine whether your generalization systems are correct. This is something that must be taken into account when generating a hypothesis and designing the experiment.

The other option, if the sample groups are small, is to use proximal similarity and restrict your generalization. This is where you accept that a limited sample group cannot represent all of the population.

If you sampled children from one town, it is dangerous to assume that it represents all children. It is, however, reasonable to assume that the results should apply to a similar sized town with a similar socioeconomic class. This is not perfect, but certainly contains more external validity and would be an acceptable generalization.

Types of Sampling: Sampling Methods with Examples

Sampling is a technique of selecting individual members or a subset of the population to make statistical inferences from them and estimate characteristics of the whole population. Different sampling methods are widely used by researchers in market research so that they do not need to research the entire population to collect actionable insights.

It is also a time-convenient and a cost-effective method and hence forms the basis of any research design . Sampling techniques can be used in a research survey software for optimum derivation.

For example, if a drug manufacturer would like to research the adverse side effects of a drug on the country’s population, it is almost impossible to conduct a research study that involves everyone. In this case, the researcher decides a sample of people from each demographic and then researches them, giving him/her indicative feedback on the drug’s behavior.

Types of sampling: sampling methods

Sampling in market research is of two types – probability sampling and non-probability sampling. Let’s take a closer look at these two methods of sampling.

  1. Probability sampling:Probability sampling is a sampling technique where a researcher sets a selection of a few criteria and chooses members of a population randomly. All the members have an equal opportunity to be a part of the sample with this selection parameter.
  2. Non-probability sampling: In non-probability sampling, the researcher chooses members for research at random. This sampling method is not a fixed or predefined selection process. This makes it difficult for all elements of a population to have equal opportunities to be included in a sample.

In this blog, we discuss the various probability and non-probability sampling methods that you can implement in any market research study.

Types of probability sampling with examples:

Probability sampling is a sampling technique in which researchers choose samples from a larger population using a method based on the theory of probability. This sampling method considers every member of the population and forms samples based on a fixed process.

For example, in a population of 1000 members, every member will have a 1/1000 chance of being selected to be a part of a sample. Probability sampling eliminates bias in the population and gives all members a fair chance to be included in the sample.

There are four types of probability sampling techniques:

  • Simple random sampling: One of the best probability sampling techniques that helps in saving time and resources, is the Simple Random Sampling method. It is a reliable method of obtaining information where every single member of a population is chosen randomly, merely by chance. Each individual has the same probability of being chosen to be a part of a sample.
    For example, in an organization of 500 employees, if the HR team decides on conducting team building activities, it is highly likely that they would prefer picking chits out of a bowl. In this case, each of the 500 employees has an equal opportunity of being selected.
  • Cluster sampling:Cluster sampling is a method where the researchers divide the entire population into sections or clusters that represent a population. Clusters are identified and included in a sample based on demographic parameters like age, sex, location, etc. This makes it very simple for a survey creator to derive effective inference from the feedback.
    For example, if the United States government wishes to evaluate the number of immigrants living in the Mainland US, they can divide it into clusters based on states such as California, Texas, Florida, Massachusetts, Colorado, Hawaii, etc. This way of conducting a survey will be more effective as the results will be organized into states and provide insightful immigration data.
  • Systematic sampling: Researchers use the systematic sampling method to choose the sample members of a population at regular intervals. It requires the selection of a starting point for the sample and sample size that can be repeated at regular intervals. This type of sampling method has a predefined range, and hence this sampling technique is the least time-consuming.
    For example, a researcher intends to collect a systematic sample of 500 people in a population of 5000. He/she numbers each element of the population from 1-5000 and will choose every 10th individual to be a part of the sample (Total population/ Sample Size = 5000/500 = 10).
  • Stratified random sampling:Stratified random sampling is a method in which the researcher divides the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized and then draw a sample from each group separately.
    For example, a researcher looking to analyze the characteristics of people belonging to different annual income divisions will create strata (groups) according to the annual family income. Eg – less than $20,000, $21,000 – $30,000, $31,000 to $40,000, $41,000 to $50,000, etc. By doing this, the researcher concludes the characteristics of people belonging to different income groups. Marketers can analyze which income groups to target and which ones to eliminate to create a roadmap that would bear fruitful results.

Uses of probability sampling

There are multiple uses of probability sampling:

  • Reduce Sample Bias: Using the probability sampling method, the bias in the sample derived from a population is negligible to non-existent. The selection of the sample mainly depicts the understanding and the inference of the researcher. Probability sampling leads to higher quality data collection as the sample appropriately represents the population.
  • Diverse Population: When the population is vast and diverse, it is essential to have adequate representation so that the data is not skewed towards one demographic . For example, if Square would like to understand the people that could make their point-of-sale devices, a survey conducted from a sample of people across the US from different industries and socio-economic backgrounds helps.
  • Create an Accurate Sample: Probability sampling helps the researchers plan and create an accurate sample. This helps to obtain well-defined data.

Types of non-probability sampling with examples

The non-probability method is a sampling method that involves a collection of feedback based on a researcher or statistician’s sample selection capabilities and not on a fixed selection process. In most situations, the output of a survey conducted with a non-probable sample leads to skewed results, which may not represent the desired target population. But, there are situations such as the preliminary stages of research or cost constraints for conducting research, where non-probability sampling will be much more useful than the other type.

Four types of non-probability sampling explain the purpose of this sampling method in a better manner:

  • Convenience sampling: This method is dependent on the ease of access to subjects such as surveying customers at a mall or passers-by on a busy street. It is usually termed as convenience sampling , because of the researcher’s ease of carrying it out and getting in touch with the subjects. Researchers have nearly no authority to select the sample elements, and it’s purely done based on proximity and not representativeness. This non-probability sampling method is used when there are time and cost limitations in collecting feedback. In situations where there are resource limitations such as the initial stages of research, convenience sampling is used.
    For example, startups and NGOs usually conduct convenience sampling at a mall to distribute leaflets of upcoming events or promotion of a cause – they do that by standing at the mall entrance and giving out pamphlets randomly.
  • Judgmental or purposive sampling:Judgemental or purposive samples are formed by the discretion of the researcher. Researchers purely consider the purpose of the study, along with the understanding of the target audience. For instance, when researchers want to understand the thought process of people interested in studying for their master’s degree. The selection criteria will be: “Are you interested in doing your masters in …?” and those who respond with a “No” are excluded from the sample.
  • Snowball sampling:Snowball sampling is a sampling method that researchers apply when the subjects are difficult to trace. For example, it will be extremely challenging to survey shelterless people or illegal immigrants. In such cases, using the snowball theory, researchers can track a few categories to interview and derive results. Researchers also implement this sampling method in situations where the topic is highly sensitive and not openly discussed—for example, surveys to gather information about HIV Aids. Not many victims will readily respond to the questions. Still, researchers can contact people they might know or volunteers associated with the cause to get in touch with the victims and collect information.
  • Quota sampling: In Quota sampling , the selection of members in this sampling technique happens based on a pre-set standard. In this case, as a sample is formed based on specific attributes, the created sample will have the same qualities found in the total population. It is a rapid method of collecting samples.

Uses of non-probability sampling

Non-probability sampling is used for the following:

  • Create a hypothesis: Researchers use the non-probability sampling method to create an assumption when limited to no prior information is available. This method helps with the immediate return of data and builds a base for further research.
  • Exploratory research: Researchers use this sampling technique widely when conducting qualitative research, pilot studies, or exploratory research .
  • Budget and time constraints: The non-probability method when there are budget and time constraints, and some preliminary data must be collected. Since the survey design is not rigid, it is easier to pick respondents at random and have them take the survey or questionnaire.

How do you decide on the type of sampling to use?

For any research, it is essential to choose a sampling method accurately to meet the goals of your study. The effectiveness of your sampling relies on various factors. Here are some steps expert researchers follow to decide the best sampling method.

  • Jot down the research goals. Generally, it must be a combination of cost, precision, or accuracy.
  • Identify the effective sampling techniques that might potentially achieve the research goals.
  • Test each of these methods and examine whether they help in achieving your goal.
  • Select the method that works best for the research.

Difference between probability sampling and non-probability sampling methods

We have looked at the different types of sampling methods above and their subtypes. To encapsulate the whole discussion, though, the significant differences between probability sampling methods and non-probability sampling methods are as below:

Making Connections: Sociology in the Real World

When Is Sharing Not Such a Good Idea?

Choosing a research methodology depends on a number of factors, including the purpose of the research and the audience for whom the research is intended. If we consider the type of research that might go into producing a government policy document on the effectiveness of safe injection sites for reducing the public health risks of intravenous drug use, we would expect public administrators to want “hard” (i.e., quantitative) evidence of high reliability to help them make a policy decision. The most reliable data would come from an experimental or quasi-experimental research model in which a control group can be compared with an experimental group using quantitative measures.

This approach has been used by researchers studying InSite in Vancouver (Marshall et al. 2011 Wood et al. 2006). InSite is a supervised safe-injection site where heroin addicts and other intravenous drug users can go to inject drugs in a safe, clean environment. Clean needles are provided and health care professionals are on hand to intervene in the case of overdose or other medical emergency. It is a controversial program both because heroin use is against the law (the facility operates through a federal ministerial exemption) and because the heroin users are not obliged to quit using or seek therapy. To assess the effectiveness of the program, researchers compared the risky usage of drugs in populations before and after the opening of the facility and geographically near and distant to the facility. The results from the studies have shown that InSite has reduced both deaths from overdose and risky behaviours, such as the sharing of needles, without increasing the levels of crime associated with drug use and addiction.

On the other hand, if the research question is more exploratory (for example, trying to discern the reasons why individuals in the crack smoking subculture engage in the risky activity of sharing pipes), the more nuanced approach of fieldwork is more appropriate. The research would need to focus on the subcultural context, rituals, and meaning of sharing pipes, and why these phenomena override known health concerns. Graduate student Andrew Ivsins at the University of Victoria studied the practice of sharing pipes among 13 habitual users of crack cocaine in Victoria, B.C. (Ivsins 2010). He met crack smokers in their typical setting downtown and used an unstructured interview method to try to draw out the informal norms that lead to sharing pipes. One factor he discovered was the bond that formed between friends or intimate partners when they shared a pipe. He also discovered that there was an elaborate subcultural etiquette of pipe use that revolved around the benefit of getting the crack resin smokers left behind. Both of these motives tended to outweigh the recognized health risks of sharing pipes (such as hepatitis) in the decision making of the users. This type of research was valuable in illuminating the unknown subcultural norms of crack use that could still come into play in a harm reduction strategy such as distributing safe crack kits to addicts.

Participant Observation

In 2000, a comic writer named Rodney Rothman wanted an insider’s view of white-collar work. He slipped into the sterile, high-rise offices of a New York “dot com” agency. Every day for two weeks, he pretended to work there. His main purpose was simply to see if anyone would notice him or challenge his presence. No one did. The receptionist greeted him. The employees smiled and said good morning. Rothman was accepted as part of the team. He even went so far as to claim a desk, inform the receptionist of his whereabouts, and attend a meeting. He published an article about his experience in The New Yorker called “My Fake Job” (2000). Later, he was discredited for allegedly fabricating some details of the story and The New Yorker issued an apology. However, Rothman’s entertaining article still offered fascinating descriptions of the inside workings of a “dot com” company and exemplified the lengths to which a sociologist will go to uncover material.

Rothman had conducted a form of study called participant observation, in which researchers join people and participate in a group’s routine activities for the purpose of observing them within that context. This method lets researchers study a naturally occurring social activity without imposing artificial or intrusive research devices, like fixed questionnaire questions, onto the situation. A researcher might go to great lengths to get a firsthand look into a trend, institution, or behaviour. Researchers temporarily put themselves into “native” roles and record their observations. A researcher might work as a waitress in a diner, or live as a homeless person for several weeks, or ride along with police officers as they patrol their regular beat. Often, these researchers try to blend in seamlessly with the population they study, and they may not disclose their true identity or purpose if they feel it would compromise the results of their research.

Figure 2.7. Is she a working waitress or a sociologist conducting a study using participant observation? (Photo courtesy of Zoetnet/flickr)

At the beginning of a field study, researchers might have a question: “What really goes on in the kitchen of the most popular diner on campus?” or “What is it like to be homeless?” Participant observation is a useful method if the researcher wants to explore a certain environment from the inside. Field researchers simply want to observe and learn. In such a setting, the researcher will be alert and open minded to whatever happens, recording all observations accurately. Soon, as patterns emerge, questions will become more specific, observations will lead to hypotheses, and hypotheses will guide the researcher in shaping data into results. In a study of small-town America conducted by sociological researchers John S. Lynd and Helen Merrell Lynd, the team altered their purpose as they gathered data. They initially planned to focus their study on the role of religion in American towns. As they gathered observations, they realized that the effect of industrialization and urbanization was the more relevant topic of this social group. The Lynds did not change their methods, but they revised their purpose. This shaped the structure of Middletown: A Study in Modern American Culture, their published results (Lynd and Lynd 1959).

Figure 2.8. A classroom in Muncie, Indiana, in 1917, five years before John and Helen Lynd began researching this “typical” American community. (Photo courtesy of Don O’Brien/flickr)

The Lynds were upfront about their mission. The townspeople of Muncie, Indiana, knew why the researchers were in their midst. But some sociologists prefer not to alert people to their presence. The main advantage of covert participant observation is that it allows the researcher access to authentic, natural behaviours of a group’s members. The challenge, however, is gaining access to a setting without disrupting the pattern of others’ behaviour. Becoming an inside member of a group, organization, or subculture takes time and effort. Researchers must pretend to be something they are not. The process could involve role playing, making contacts, networking, or applying for a job. Once inside a group, some researchers spend months or even years pretending to be one of the people they are observing. However, as observers, they cannot get too involved. They must keep their purpose in mind and apply the sociological perspective. That way, they illuminate social patterns that are often unrecognized. Because information gathered during participant observation is mostly qualitative, rather than quantitative, the end results are often descriptive or interpretive. The researcher might present findings in an article or book, describing what he or she witnessed and experienced.

This type of research is what journalist Barbara Ehrenreich conducted for her book Nickel and Dimed. One day over lunch with her editor, as the story goes, Ehrenreich mentioned an idea. How can people exist on minimum-wage work? How do low-income workers get by? she wondered. Someone should do a study. To her surprise, her editor responded, Why don’t you do it? That is how Ehrenreich found herself joining the ranks of the low-wage service sector. For several months, she left her comfortable home and lived and worked among people who lacked, for the most part, higher education and marketable job skills. Undercover, she applied for and worked minimum wage jobs as a waitress, a cleaning woman, a nursing home aide, and a retail chain employee. During her participant observation, she used only her income from those jobs to pay for food, clothing, transportation, and shelter. She discovered the obvious: that it’s almost impossible to get by on minimum wage work. She also experienced and observed attitudes many middle- and upper-class people never think about. She witnessed firsthand the treatment of service work employees. She saw the extreme measures people take to make ends meet and to survive. She described fellow employees who held two or three jobs, worked seven days a week, lived in cars, could not pay to treat chronic health conditions, got randomly fired, submitted to drug tests, and moved in and out of homeless shelters. She brought aspects of that life to light, describing difficult working conditions and the poor treatment that low-wage workers suffer.

Figure 2.9. Field research happens in real locations. What type of environment do work spaces foster? What would a sociologist discover after blending in? (Photo courtesy of drewzhrodague/flickr)


Ethnography is the extended observation of the social perspective and cultural values of an entire social setting. Researchers seek to immerse themselves in the life of a bounded group, by living and working among them. Often ethnography involves participant observation, but the focus is the systematic observation of an entire community.

The heart of an ethnographic study focuses on how subjects view their own social standing and how they understand themselves in relation to a community. An ethnographic study might observe, for example, a small Newfoundland fishing town, an Inuit community, a village in Thailand, a Buddhist monastery, a private boarding school, or Disney World. These places all have borders. People live, work, study, or vacation within those borders. People are there for a certain reason and therefore behave in certain ways and respect certain cultural norms. An ethnographer would commit to spending a determined amount of time studying every aspect of the chosen place, taking in as much as possible, and keeping careful notes on his or her observations.

A sociologist studying a tribe in the Amazon might learn the language, watch the way villagers go about their daily lives, ask individuals about the meaning of different aspects of activity, study the group’s cosmology and then write a paper about it. To observe a spiritual retreat centre, an ethnographer might sign up for a retreat and attend as a guest for an extended stay, observe and record how people experience spirituality in this setting, and collate the material into results.

The Mystery of the Bones

As a group, visit the following sites to gain an understanding of forensic anthropology and what bones (or remains) can tell you about the deceased. Be prepared to take a quiz (as a group) when you are finished. Write all answers on a separate page, you can turn in a single page for your entire group.

Investigative Techniques of Forensic Anthropology (
Mouse over the skeleton to answer these..

1. What can the teeth tell you about the deceased?
2. How can the skull be used to determine age?
3. How is the pelvis of a female different from the pelvis of a male?
4. The hand bones can help you determine what about the deceased?

Explore Forensics ( ) - most can be found at the link: Analyzing the body

1. What is the first thing a forensic scientist looks at to identify a deceased?
2. Where is the most accurate place to take the body temperature? Suppose a body is found and its temperature is recorded at 34 degrees celcius, how long has the body been dead?
3. Why might a corpse be exhumed?
4. What insect is used to determine time of death? What type of scientist studies these insects?
5. What is rigormortis and how long does it last?
6. What is lividity?
7. What are the four categories of death?

Skeleton Keys --> Bone Basics

1. What is the last bone to complete its growth?
2. How are teeth used to estimate age?
3. What is bone "remodeling" and how can it be used to determine age?
4. What is the sciatic notch? How can it be used to determine gender?

Forensic Case Files

5. Browse the cases and choose one that interests you. Describe the case and the key evidence used to solve it.


When you have reviewed all of the links and feel confident (know the answers to the questions) see your teacher to get the quiz. You will take the quiz as a group to receive your "Medical Examiner License" that will allow you to proceed to the next section.

5 Research-Backed Studying Techniques

Teachers can guide students to avoid ineffective studying habits in favor of ones that will increase their learning outcomes.

Too often people imagine that long hours of studying are the best path to being a model, straight-A student. Yet research shows that highly successful students actually spend less time studying than their peers do—they just study more effectively.

Teachers can help all students learn to more effectively use the time they spend studying by sharing research-proven techniques.

Study Less, With Greater Intensity

In this era of social media and digital distractions, many students—and adults—do a lot of multitasking. But there is no such thing as successful multitasking, because much of the time spent is wasted on context switching, where the brain has to restart and refocus.

Consider the formula “work accomplished = intensity of focus X time spent.” A student who is studying for AP Biology but also checks his texts and scrolls through Instagram has a low intensity of focus—say a 3. Though he spends 3 hours “studying,” his work accomplished is only a 9.

On the other hand, a student who takes steps to focus solely on AP Biology has a high-intensity of focus—a 10. Though she spends only an hour studying, she accomplishes more than her distracted classmate did in 3 hours.

Highly successful students have generally learned to avoid multitasking. Instead of spending a lot of time doing low-intensity work with numerous distractions, these students work for shorter periods at higher intensity, without any distractions from email, social media, etc. Their studying is more effective and leads to greater achievement gains.

Ineffective Learning Techniques

Many students use learning techniques that are time consuming and give the illusion of mastery. They become familiar with ideas and information in preparation for a test, but forget it a week later because their learning techniques never led to long-term learning.

Ineffective techniques include:

  • Studying for long periods of time
  • Studying a single subject for a long period of time and repeating phrases over and over to memorize them (known as massed practice)
  • Reviewing one topic repeatedly before moving onto another topic (blocked practice) in a text and then reviewing

5 High-Intensity Study Habits

Researchers have found that the following techniques increase sustainable learning and retention when incorporated in students’ daily study habits. These techniques are difficult and require effort, and they slow down learning. Initially the learning gains seem to be smaller than with some ineffective practices. However, these techniques lead to long-term mastery.

The book Make It Stick identifies several research-proven studying techniques.

1. Pre-test: When students practice answering questions, even incorrectly, before learning the content, their future learning is enhanced. Research has shown that pre-testing improves post-test results more than spending the same amount of time studying.

2. Spaced practice: Spacing out study sessions—focusing on a topic for a short period on different days—has been shown to improve retention and recall more than massed practice. The book How We Learn explains that spaced practice can feel difficult due to an initial forgetting of knowledge—reacquiring that knowledge takes effort.

Creating flash cards that can be used for spaced practice and self-quizzing is effective. Students should create different piles when reviewing the flash cards. The cards they’re able to answer immediately should be placed in a pile to review three days later those answered with some difficulty should be reviewed two days later and those that they answered incorrectly should be reviewed the next day.

3. Self-quizzing: Testing has a negative connotation in this era of standardized testing, but it is a form of active retrieval practice. Encourage students to make test questions for themselves as they learn a new concept, thinking about the types of questions you might ask on a quiz or test. They should incorporate these quizzes into their study sessions, answering every question, even those they believe they know well.

4. Interleaving practice: Students may rely on blocked practice, studying a set of problems—such as multiplication problems—as a group until they feel mastery. A more effective method of studying is to work on a set of problems that are related but not all of the same kind—for example, a set of math word problems that call for addition, subtraction, multiplication, or division. The consecutive problems cannot be solved with the same strategy. This is more effective than doing one multiplication problem after another.

5. Paraphrasing and reflecting: Many of us have read a few paragraphs in a textbook only to realize that we didn’t retain a single concept or key point presented in those paragraphs. To show your students how to combat this, have them utilize intentional learning strategies. These include relating what is being learned to prior knowledge, thinking about how they would explain the content to a 5-year-old, and reflecting on and asking questions about the content.

There is a delicate balance between a realistic research statement where you promise to work on problems you really think you can solve and over-reaching or dabbling in too many subject areas. Select an over-arching theme for your research statement and leave miscellaneous ideas or projects out. Everyone knows that you will work on more than what you mention in this statement.

  • A longer version (five–15 pages) can be brought to your interview. (Check with your advisor to see if this is necessary.)
  • You may be asked to describe research plans and budget in detail at the campus interview. Be prepared.
  • Include laboratory needs (how much budget you need for equipment, how many grad assistants, etc.) to start up the research.

Watch the video: DARAUF, DAFÜR, DAMIT, DARÜBER и. ЧТО ЭТО?! Deutsch mit Yehor (February 2023).